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Reducing Dairy Data Inconsistency Through Regional Modeling Approach (rma): a Case from North-western Part of Bangladesh

MM Uddin
Dairy Nutrition, Economics, Environment and Marketing, Department of Animal Nutrition, Bangladesh Agricultural University, Mymensingh 2202

A Akter
Dairy Nutrition, Economics, Environment and Marketing, Department of Animal Nutrition, Bangladesh Agricultural University, Mymensingh 2202

BB Bruemmer
Department of Agricultural Economics and Rural Development, University of Goettingen, Germany

MR Islam
Rural Development Academy (RDA), Bogura

MS Palash
Department of Agribusiness and Marketing. Bangladesh Agricultural University, Mymensingh

ABM Khaleduzzaman
Department of Livestock Services (DLS), Ministry of Fisheries and Livestock (MoFL) Dhaka

MN Sultana
Research group: Dairy Nutrition, Economics, Environment and Marketing, Department of Animal Nutrition, Bangladesh Agricultural University, Mymensingh.

M Tanzin
Research group: Dairy Nutrition, Economics, Environment and Marketing, Department of Animal Nutrition, Bangladesh Agricultural University, Mymensingh; Rural Development Academy (RDA), Bogura.

Abstract/ Executive Summary:

In Bangladesh, the transformation of dairy farming from livelihood-oriented to the enterprise-driven farming system might require a deeper understanding of the regional differences in terms of regional potential for further dairy development. This, however, entails detailed data on dairy farms at the regional level. Since the data are relatively very scarce on one hand and on the other hand, even available, are contradicting among various sources in terms of data accuracy and precision, the application of the regional modeling on the data and extrapolates to the national data and vice-versa is one of the ways to identify the possible options to improve the data availability and quality. Considering this, the current study was undertaken to assess the data inconsistency by comparing the dairy herd structure and its milk production at the regional level and propose a validation tool to arrive at the national data by using the regional findings. The International Farm Comparison Network (IFCN) Regional Modeling Approach (RMA) along with the locally developed Integrated Dairy Research Network (IDRN) farm model was used. The primary data was collected from three divisions (9 districts) from the North-Western part of the country. The results revealed that the proportion of household farms dominates over family and business farms while considering the total dairy cow as a unit for defining the farm type. The share of the cross-bred cows to the local cows is 74.6% and 24.4%, respectively. However, the proportion of lactating cows over dry cows and heifer seems to be higher in local cows (48.8%) than crossbreed cows (34.2%). The average milk production for all regions is 4.49 lit/day/cow while that for crossbreed is 6.23 lit and local 1.71 lit/day/cow. Using the regional model and its coefficient on average milk production, herd composition, the proportion of lactating cows on total milk production of DLS and IDRN revealed that IDRN new model estimates 36.5% lower milk than the DLS in 2019 and 33.5% lower in 2018. The IDRN version 1.0 and 2.0 model difference was found to 15.4% and 18.3% lower for 2018 and 2019, respectively. The model setup, calibration, and validation are time-demanding and challenging tasks for these large sets of data, given the scale-intensive data requirements, and the need to ensure the reliability of data from multiple regions. This study concludes that regional modeling is quite useful for validating the regional share of milk production and national milk production. However, this study would recommend using standardized for data collection, validation and thus conducting a further study on the other regions and finally including all regions of the country.

Keywords: Milk production; Local and cross bred cows; Data inconsistency; Regional model; IDRN networking

Location: Dairy Nutrition, Economics, Environment and Marketing, Department of Animal Nutrition, Bangladesh Agricultural University, Mymensingh 2202

Start Date: 00-00-2018

End Date: 00-00-2019

Program Area: Resource Development and Management

Commodity: Dairy, Modeling

Objectives:

Therefore, this study has been aiming at assessment of the dairy data inconsistency by comparing the dairy herd structure and its milk production at cow level on the regional level and proposes a validation tool to arrive at the national data by using the regional findings.

Methodology:

This study was carried out using the International Farm Comparison Network (IFCN) RMA which is, however, calibrated with a locally developed Integrated Dairy Research Network (IDRN) farm model. The IFCN model is based on the real-time farm econometrics, dynamic, multi-country, and multi-stakeholder model for the global dairy sector and dairy farm while the IDRN is focused more on the regional and local dairy sector. The combination of both models provides an outstanding opportunity to make in-depth analyses on the targeted research issues, especially in the case where the data are scarce. To make a comprehensive overview of the regional dynamics in the herd structure and milk productivity, it is also important to adopt the concept of dairy networking. The IFCN is a global network that connects 80 research partners from 120 countries and 110 dairy companies under the auspices of the University of Kiel, Germany. This network has strong tools and models for analyzing a complete picture of the dairy sector, dairy market, dairy farm, production systems, feeding system, market integration, forecasting production, demand, and market outlook. This model clustering on herd structure, dairy farm within-herd size class, milk production at the global and regional levels. However, the regional data from different countries are on the aggregate level, and for Bangladesh only to the Divisional level. This limitation is, however, can be overcome by using the IDRN farm model where the model is extended to district and sub-district levels with a possibility to extend the model to Union and Village level. This requires the IDRN to be adopted from a project-based www model to a more institutional model similar to IFCN. Since IDRN is still under the development, validation, and testing phase, therefore further attempts are needed to be executed to be endorsed by the institutional level. As the data is scarce from the formal sources, the IDRN farm model can make a bridge between the formal data government agency and academic agency as this network is well connected with the global IFCN network. The IFCN model is already used in several studies.

A well-trained and having well background knowledge on livestock, particularly dairy farming, herewith called “Database Team” was assigned to collect data which was consecutively passed through a number of quality checks by the research team, expert panel, and national workshop. This is the uniqueness of the IDRN data and model compared with the traditional data collection method. A very strong quality check tool is employed in every step of the data collection starting from the study design to the result publication. A pre-defined and pre-tested questionnaire was used to collect the pertinent data for this study. A total of 25 variables which have at least 1 to 10 i.e., sub-variables called “Transect Study” were used for this study. In order to cross-check and validation of the collected data and assess the regions, the IDRN check tool (following the IFCN principle) and comparing with a total of eight sources were applied for this study: i) Department of Livestock Services (DLS), ii) Bangladesh Bureau of Statistics (BBS) iii) Bangladesh Economic Review (BER) iv) Food and Agricultural Organizations (FAO) v) Integrated Dairy Research Network (IDRN) Farm Database vi) IDRN Sector Database vii) International Farm Comparison Network (IFCN) sector database and viii) Reviewing various data generated in the Animal Nutrition Analytical Laboratory and research articles on structural change and milk production. The data was analyzed using the IDRN farm model version 1.0 and MS Excel was used to manage the data.

Source of Information: Bang. J. Anim. Sci. 2020. 49 (2): 128-141

Article Link (Online Journal): DOI: https://doi.org/10.3329/bjas.v49i2.53221

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

This study proposed three types of dairy farms which are different from the traditional farm types, but this farm type is claimed as a close representation of the farming system of Bangladesh. The regional modeling results depicted that the proportion of family farms is higher while considering total livestock units and the household farm is higher while considering the total dairy cow unit. The average milk production is 4.49 lit/cow/day wherein for the local is 1.71 lit/cow/day and crossbred is 6.23 lit/cow/day. The top four milk-producing regions based on the average milk yield per cow per day are SG-51 (7.72 lit), RJ-52(7.58 lit), PB-50(6.37 lit), and JP- 41 (6.12 lit), which is divergent from the existing literature as it is quite usual for the highest milk producing region for SG-51 and PB-50. The top position for SG-51 is reflecting the reality as this region is well developed and considered as the major dairy region in Bangladesh. The inconsistency in the national-level data on the dairy sector might be considered as the key constraints for the proper decision-making process, formulating policy, and applying interventions on dairy development. The application of the regional modeling approach of IFCN and IDRN could provide broader scope for validation of the data for the dairy sector development. The regional model revealed that the northwestern part of the country is well representative of the dairy region especially the regions of the Rajshahi division with the highest milk production, such as Sirajganj and Pabna is located with a higher percentage of business farms. This study further identified some inconsistency in the data among various sources which entail taking initiatives by the government-affiliated respected data collection agency (e.g. BBS, DLS) to make coordination among them and also it would be worthy to use established methods, models, and validation tools before publishing the data to represent fact-based situation better for Bangladesh Dairy so that real intervention can be made to reach the target to become self-sufficient in milk production in near future. The external organization like FAO, IFCN, and IDRN could be well linked and endorsed with the government for increasing the precision of the data with real-time updates. Even with the fact that regional model could provide more precise information on the regional level but does not necessarily allow to extrapolate to the national level. This would require the inclusion of all districts and more sample for farm-level data, which could make a step forward which also fits with the vision and mission of the IDRN which collaboration with IFCN and DLS can play a role to support Sustainable Dairy Development in Bangladesh.

Knowledge Management: Journal